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Record W2966017254

The Care Economy: a new research framework

2019· preprint· fr· W2966017254 on OpenAlexaff
Ito Peng

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2019
Typepreprint
Languagefr
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSharing economyBusinessEconomicsComputer scienceWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

Care economy refers to the sector of economic activities, both paid and unpaid, related to the provisions of social and material care, which contribute to nurturing and supporting the present and future populations. Broadly, it includes direct and indirect care of children, the elderly and the disabled, health care, education, and as well, financial and other personal and domestic services aimed at supporting and enhancing individual well-being. Although largely invisible and scarcely accounted in national account systems, such as GDP, care and care work is increasingly recognized as essential for the maintenance of capability and well-being of individuals, and for the functioning of society and the economy. In almost all high- and middle-income countries the combination of the shift from an industrial/manufacturing to a\nservice-based economy and the steady socio-demographic changes over the last several decades have made care economy an increasingly relevant social, economic and political issue today. Yet, despite growing awareness, the concept of the care economy remains ambiguous and the research on the topic germinal. \nThe objectives of this paper are to: 1) trace and elucidate the ideas around the care economy; 2) analyze key concepts and debates around the idea of the care economy that may contribute to future research; and 3) discuss a potential research and policy agenda for understanding care economies today. I draw mostly from feminist research within the fields of social policy and welfare states, economy, sociology and political economy, highlighting some of the key debates and areas of convergence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.009
Science and technology studies0.0060.053
Scholarly communication0.0200.036
Open science0.0030.009
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.308
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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